Question 1

Principal components are usually easier to interpret than the cluster components.

Accepted Answer

A) True 
 B)False

Question 2

Which statement is not true about cluster analysis?

Accepted Answer

A) Cluster analysis is a technique for analyzing data when the criterion or dependent variable is categorical and the independent variables are interval in nature. 
B) Cluster analysis is also called classification analysis or numerical taxonomy. 
C) Groups or clusters are suggested by the data, not defined a priori. 
D) Objects in each cluster tend to be similar to each other and dissimilar to objects in the other clusters. 
A) Cluster analysis is a technique for analyzing data when the criterion or dependent variable is categorical and the independent variables are interval in nature. 
B) Cluster analysis is also called classification analysis or numerical taxonomy. 
C) Groups or clusters are suggested by the data, not defined a priori. 
D) Objects in each cluster tend to be similar to each other and dissimilar to objects in the other clusters.

Question 3

To reduce the number of variables, a large set of variables can often be replaced by the set of cluster components.

Accepted Answer

A) True 
 B)False

Question 4

The primary objective of cluster analysis is to classify objects into relatively homogeneous groups.

Accepted Answer

A) True 
 B)False

Question 5

Most ________ methods are heuristics based on algorithms.

Accepted Answer

A) factor analysis 
B) discriminant analysis 
C) clustering 
D) analysis of variance 
A) factor analysis 
B) discriminant analysis 
C) clustering 
D) analysis of variance

Question 6

In cluster analysis, the set of variables selected should describe the similarity between objects in terms that are relevant to the marketing research problem.

Accepted Answer

A) True 
 B)False

Question 7

In cluster analysis, objects with larger distances between them are more similar to each other than are those at smaller distances.

Accepted Answer

A) True 
 B)False

Question 8

Which of the following is not a disadvantage of nonhierarchical clustering procedures?

Accepted Answer

A) The number of clusters must be pre-specified. 
B) The selection of cluster centers is arbitrary. 
C) The procedures do not work well when the clusters are poorly defined. 
D) All of the above are disadvantages. 
A) The number of clusters must be pre-specified. 
B) The selection of cluster centers is arbitrary. 
C) The procedures do not work well when the clusters are poorly defined. 
D) All of the above are disadvantages.

Question 9

Choice of a clustering method and choice of a distance measure are interrelated.

Accepted Answer

A) True 
 B)False

Question 10

If you are performing cluster analysis on the same data using different distance measures and then comparing the results across measures to determine stability of the solutions, you are at which stage of the cluster analysis process?

Accepted Answer

A) interpreting and profiling the clusters 
B) assessing reliability and validity 
C) deciding on the number of clusters 
D) selecting a clustering procedure 
A) interpreting and profiling the clusters 
B) assessing reliability and validity 
C) deciding on the number of clusters 
D) selecting a clustering procedure

Question 11

Nonhierarchical clustering is faster than hierarchical methods.

Accepted Answer

A) True 
 B)False

Question 12

A ________ is a lower-triangle matrix containing pairwise distances between objects or cases.

Accepted Answer

A) classification matrix 
B) correlation matrix 
C) similarity/distance coefficient matrix 
D) factor matrix 
A) classification matrix 
B) correlation matrix 
C) similarity/distance coefficient matrix 
D) factor matrix

Question 13

In non-hierarchical clustering, plotting the ratio of total within-group variance to between-group variance against the number of clusters is useful if you are ________.

Accepted Answer

A) interpreting and profiling the clusters 
B) assessing the validity of clustering 
C) deciding on the number of clusters 
D) both B and C 
A) interpreting and profiling the clusters 
B) assessing the validity of clustering 
C) deciding on the number of clusters 
D) both B and C

Question 14

________ is a clustering procedure where each object starts out in a separate cluster.

Accepted Answer

A) Non-hierarchical clustering 
B) Hierarchical clustering 
C) Divisive clustering 
D) Agglomerative clustering 
A) Non-hierarchical clustering 
B) Hierarchical clustering 
C) Divisive clustering 
D) Agglomerative clustering

Question 15

The parallel threshold method differs from the other two non-hierarchical clustering procedures in that the objects can later be reassigned to clusters to optimize an overall criterion.

Accepted Answer

A) True 
 B)False

Question 16

Use of different distance measures may lead to different clustering results. Hence, it is advisable to use different measures and compare the results.

Accepted Answer

A) True 
 B)False

Question 17

In the TwoStep procedure, the euclidean measure can be used only when all of the variables are ordinal.

Accepted Answer

A) True 
 B)False

Question 18

The ________ method is based on the maximum distance or the furthest neighbor approach.

Accepted Answer

A) single linkage 
B) medium linkage 
C) complete linkage 
D) average linkage 
A) single linkage 
B) medium linkage 
C) complete linkage 
D) average linkage

Question 19

Formal procedures for assessing the reliability and validity of clustering are simple and should be undertaken.

Accepted Answer

A) True 
 B)False

Question 20

What suggested guidelines researchers can use when deciding on the number of clusters?

Accepted Answer

Although there are no hard and fast rule

Exam 20: Cluster Analysis

Principal components are usually easier to interpret than the cluster components.

Which statement is not true about cluster analysis?

To reduce the number of variables, a large set of variables can often be replaced by the set of cluster components.

The primary objective of cluster analysis is to classify objects into relatively homogeneous groups.

Most ________ methods are heuristics based on algorithms.

In cluster analysis, the set of variables selected should describe the similarity between objects in terms that are relevant to the marketing research problem.

In cluster analysis, objects with larger distances between them are more similar to each other than are those at smaller distances.

Which of the following is not a disadvantage of nonhierarchical clustering procedures?

Choice of a clustering method and choice of a distance measure are interrelated.

If you are performing cluster analysis on the same data using different distance measures and then comparing the results across measures to determine stability of the solutions, you are at which stage of the cluster analysis process?

Nonhierarchical clustering is faster than hierarchical methods.

A ________ is a lower-triangle matrix containing pairwise distances between objects or cases.

In non-hierarchical clustering, plotting the ratio of total within-group variance to between-group variance against the number of clusters is useful if you are ________.

________ is a clustering procedure where each object starts out in a separate cluster.

The parallel threshold method differs from the other two non-hierarchical clustering procedures in that the objects can later be reassigned to clusters to optimize an overall criterion.

Use of different distance measures may lead to different clustering results. Hence, it is advisable to use different measures and compare the results.

In the TwoStep procedure, the euclidean measure can be used only when all of the variables are ordinal.

The ________ method is based on the maximum distance or the furthest neighbor approach.

Formal procedures for assessing the reliability and validity of clustering are simple and should be undertaken.

What suggested guidelines researchers can use when deciding on the number of clusters?

Introduction to Marketing Research

Defining the Marketing Research Problem and Developing an Approach

Research Design

Exploratory Research Design: Secondary Data

Exploratory Research Design: Qualitative Research

Descriptive Research Design: Survey and Observation

Causal Research Design: Experimentation

Measurement and Scaling: Fundamentals and Comparative Scaling

Measurement and Scaling: Noncomparative Scaling Techniques

Questionnaire and Form Design

Sampling: Design and Procedures

Sampling: Final and Initial Sample Size Determination

Fieldwork

Data Preparation

Frequency Distribution, Cross-Tabulation, and Hypothesis Testing

Analysis of Variance and Covariance

Correlation and Regression

Discriminant and Logit Analysis

Factor Analysis

Multidimensional Scaling and Conjoint Analysis

Structural Equation Modeling and Path Analysis

Report Preparation and Presentation

International Marketing Research

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